# director

> director — fdmtl-director. Use this tool when you need to manage and execute MCP Playbooks for AI agents, solving issues related to automated workflows and task orchestration. It provides an interface to input playbook configurations and outputs execution results, leveraging git for version control. Ideal for use cases requiring automated task management and workflow optimization in AI-driven environments.

Canonical page: https://skillsregistry.net/skills/fdmtl-director  
JSON: https://api.skillsregistry.net/v1/skills/fdmtl-director

## Description

MCP Playbooks for AI agents

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-27

## Source

- **Source listing:** [GitHub](https://github.com/fdmtl/director)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "fdmtl-director"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fdmtl-director` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fdmtl-director/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt